Supports data integration, harmonization, curation, and analytic infrastructure to enable the evaluation and use of measures across studies.
Core Lead:
Sy-Miin Chow, Ph.D.
Purpose
Identifies clinical and diagnostic indicators that can serve as anchors for interpreting cognitive change in OMNI ADRD datasets.
Outputs
Curated inventory of clinically relevant markers and recommendations for defining meaningful change at the individual level.
Why this matters
Detecting change is only useful if it can be interpreted. Linking digital measures to clinical outcomes is essential for making results actionable in research and trials.
WG Lead: Andrea Cataldo, PhD
WG Lead: Jason Hassenstab, PhD
WG Lead: Joey Mukherjee, PhD
Emily Trittschuh, PhD
Timothy Brearly, PsyD
Kaylee Litson, PhD
Jonathan Hakun, PhD
Purpose
Develops and evaluates statistical methods for measuring cognitive change across studies and populations.
Outputs
Standardized analytic tools and scripts for modeling change, including approaches that address practice effects, variability, and group differences.
Why this matters
Different analytic methods can lead to very different conclusions about change. This work helps establish more reliable and comparable approaches across studies.
WG Lead: Michael Hunter, PhD
WG Lead: James Uanhoro, PhD
Zita Oravecz, PhD
Chun Wang, PhD
Seo-Eun Choi, PhD
Hyungeun Oh, MA
Nduka Boika, PhD
Vikram Goud Thorupunuri
Purpose
Creates methods for integrating cognitive data across studies with different designs, measures, and populations.
Outputs
Guidance and analytic approaches for linking datasets using common-person and common-item strategies.
Why this matters
No single study is large or diverse enough to answer all key questions. Harmonization allows investigators to combine data across studies to improve power, generalizability, and discovery.
WG Lead: Chun Wang, PhD
WG Lead: Richard Jones, ScD
WG Lead: Seo-Eun Choi, PhD
John Felt, PhD
Paul Crane, MD
Douglas Tommet, MS
Purpose
Builds a centralized system for organizing and visualizing metadata across OMNI ADRD studies and measures.
Outputs
An accessible dashboard describing study designs, measures, assessment frequency, and data characteristics.
Why this matters
Investigators often spend substantial time just figuring out what data exist and how they were collected. This work makes OMNI ADRD resources easier to find, understand, and use.
WG Lead: John Felt, PhD
WG Lead: Seo-Eun Choi, PhD
Hyungeun Oh, MA
Scott Yabiku, PhD
Nelson Roque, PhD
Sy-Miin Chow, PhD
